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cs.RO2024
Fusing Multi-sensor Input with State Information on TinyML Brains for Autonomous Nano-drones
Luca Crupi, Elia Cereda, Daniele Palossi
Autonomous nano-drones (~10 cm in diameter), thanks to their ultra-low power TinyML-based brains, are capable of coping with real-world environments. However, due to their simplifi…
cs.RO2024
Self-Supervised Learning of Visual Robot Localization Using LED State Prediction as a Pretext Task
Mirko Nava, Nicholas Carlotti, Luca Crupi +2
We propose a novel self-supervised approach for learning to visually localize robots equipped with controllable LEDs. We rely on a few training samples labeled with position ground…
cs.RO2023
Sim-to-Real Vision-depth Fusion CNNs for Robust Pose Estimation Aboard Autonomous Nano-quadcopter
Luca Crupi, Elia Cereda, Alessandro Giusti +1
Nano-quadcopters are versatile platforms attracting the interest of both academia and industry. Their tiny form factor, i.e., 10 cm diameter, makes them particularly useful in…